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Heinz G. Stefan - One of the best experts on this subject based on the ideXlab platform.
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Modified equilibrium temperature models for cold‐water streams
Water Resources Research, 2011Co-Authors: William R. Herb, Heinz G. StefanAbstract:[1] Water temperature determines the spatial distribution of fish species, including cold-water fish such as trout, and is driven by the balance of the heat flux across the water surface and the heat flux across the sediment surface. In this study, a modified equilibrium temperature model was developed for cold-water streams that includes the effect of groundwater inflow. The modified equilibrium temperature model gives estimates of daily average stream temperature based on climate conditions, riparian shading, stream width, and groundwater input rate and temperature. For a small tributary stream with relatively uniform riparian shading, the modified equilibrium temperature was found to be a good predictor of daily average stream temperature, with a root-mean-square errors (RMSE) of 1.2°C. The modified equilibrium temperature model also gave good estimates (1.4°C RMSE) of daily average stream temperature for a larger stream when riparian shading was averaged over sufficiently long distances. A sensitivity analysis using the modified equilibrium temperature model confirmed that water temperature in cold-water streams varies strongly with riparian shading, stream width, and both groundwater inflow rate and temperature. These groundwater parameters therefore need to be taken into account when climate change impacts on stream temperature are projected. The stream temperature model developed in this study is a useful tool to characterize temperature conditions in cold-water streams with different levels of riparian shading and groundwater inputs and to assess the impact of future land use and climate change on temperature in these streams.
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modified equilibrium temperature models for cold water streams
Water Resources Research, 2011Co-Authors: William R. Herb, Heinz G. StefanAbstract:[1] Water temperature determines the spatial distribution of fish species, including cold-water fish such as trout, and is driven by the balance of the heat flux across the water surface and the heat flux across the sediment surface. In this study, a modified equilibrium temperature model was developed for cold-water streams that includes the effect of groundwater inflow. The modified equilibrium temperature model gives estimates of daily average stream temperature based on climate conditions, riparian shading, stream width, and groundwater input rate and temperature. For a small tributary stream with relatively uniform riparian shading, the modified equilibrium temperature was found to be a good predictor of daily average stream temperature, with a root-mean-square errors (RMSE) of 1.2°C. The modified equilibrium temperature model also gave good estimates (1.4°C RMSE) of daily average stream temperature for a larger stream when riparian shading was averaged over sufficiently long distances. A sensitivity analysis using the modified equilibrium temperature model confirmed that water temperature in cold-water streams varies strongly with riparian shading, stream width, and both groundwater inflow rate and temperature. These groundwater parameters therefore need to be taken into account when climate change impacts on stream temperature are projected. The stream temperature model developed in this study is a useful tool to characterize temperature conditions in cold-water streams with different levels of riparian shading and groundwater inputs and to assess the impact of future land use and climate change on temperature in these streams.
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stream temperature equilibrium temperature relationship
Water Resources Research, 2003Co-Authors: Travis Bogan, Omid Mohseni, Heinz G. StefanAbstract:[1] Equilibrium temperature is the water temperature at which the sum of all heat fluxes through the water surface is zero. It can be calculated from weather data. Mean weekly stream temperature was found to be linearly related to mean weekly equilibrium temperature above 0°C. The slopes and intercepts of the linear relationship were used to identify effects of shading, sheltering, cold water inputs (groundwater, meltwater, and deep reservoir releases) and warm water inputs (wastewater, cooling water, and lake surface water). The linearity hypothesis was confirmed for data from 596 U.S. Geological Survey stream gaging stations in the eastern and central United States. For approximately 15% (89 of 596, NSC ≥ 0.90) of stream gaging stations, weekly equilibrium temperature was a good estimator of weekly stream temperature with zero wind sheltering and sun shading. With sheltering and shading the number rose to 26% (156 of 596). For these streams the heat exchange through the water surface has the most controlling effect on stream temperatures. For the remaining 74% of streams the relationship between weekly stream temperature and weekly equilibrium temperature was also linear, but its slope was significantly less than 1.0 (even after calibration for shading and sheltering), indicating that processes other than surface heat exchange have an influence. Cold water inflows were dominant for 8% (46 of 596) of stream gaging sites. Less than 5% of all stream gaging stations showed evidence of unnatural heat inputs. Fitting an equilibrium temperature linearly to recorded stream temperatures, e.g., at a weekly timescale, can be of use to project stream temperatures under different weather-climate scenarios or to identify both natural and anthropogenic heat and hydrologic inputs to streams.
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Stream temperature‐equilibrium temperature relationship
Water Resources Research, 2003Co-Authors: Travis Bogan, Omid Mohseni, Heinz G. StefanAbstract:[1] Equilibrium temperature is the water temperature at which the sum of all heat fluxes through the water surface is zero. It can be calculated from weather data. Mean weekly stream temperature was found to be linearly related to mean weekly equilibrium temperature above 0°C. The slopes and intercepts of the linear relationship were used to identify effects of shading, sheltering, cold water inputs (groundwater, meltwater, and deep reservoir releases) and warm water inputs (wastewater, cooling water, and lake surface water). The linearity hypothesis was confirmed for data from 596 U.S. Geological Survey stream gaging stations in the eastern and central United States. For approximately 15% (89 of 596, NSC ≥ 0.90) of stream gaging stations, weekly equilibrium temperature was a good estimator of weekly stream temperature with zero wind sheltering and sun shading. With sheltering and shading the number rose to 26% (156 of 596). For these streams the heat exchange through the water surface has the most controlling effect on stream temperatures. For the remaining 74% of streams the relationship between weekly stream temperature and weekly equilibrium temperature was also linear, but its slope was significantly less than 1.0 (even after calibration for shading and sheltering), indicating that processes other than surface heat exchange have an influence. Cold water inflows were dominant for 8% (46 of 596) of stream gaging sites. Less than 5% of all stream gaging stations showed evidence of unnatural heat inputs. Fitting an equilibrium temperature linearly to recorded stream temperatures, e.g., at a weekly timescale, can be of use to project stream temperatures under different weather-climate scenarios or to identify both natural and anthropogenic heat and hydrologic inputs to streams.
Travis Bogan - One of the best experts on this subject based on the ideXlab platform.
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stream temperature equilibrium temperature relationship
Water Resources Research, 2003Co-Authors: Travis Bogan, Omid Mohseni, Heinz G. StefanAbstract:[1] Equilibrium temperature is the water temperature at which the sum of all heat fluxes through the water surface is zero. It can be calculated from weather data. Mean weekly stream temperature was found to be linearly related to mean weekly equilibrium temperature above 0°C. The slopes and intercepts of the linear relationship were used to identify effects of shading, sheltering, cold water inputs (groundwater, meltwater, and deep reservoir releases) and warm water inputs (wastewater, cooling water, and lake surface water). The linearity hypothesis was confirmed for data from 596 U.S. Geological Survey stream gaging stations in the eastern and central United States. For approximately 15% (89 of 596, NSC ≥ 0.90) of stream gaging stations, weekly equilibrium temperature was a good estimator of weekly stream temperature with zero wind sheltering and sun shading. With sheltering and shading the number rose to 26% (156 of 596). For these streams the heat exchange through the water surface has the most controlling effect on stream temperatures. For the remaining 74% of streams the relationship between weekly stream temperature and weekly equilibrium temperature was also linear, but its slope was significantly less than 1.0 (even after calibration for shading and sheltering), indicating that processes other than surface heat exchange have an influence. Cold water inflows were dominant for 8% (46 of 596) of stream gaging sites. Less than 5% of all stream gaging stations showed evidence of unnatural heat inputs. Fitting an equilibrium temperature linearly to recorded stream temperatures, e.g., at a weekly timescale, can be of use to project stream temperatures under different weather-climate scenarios or to identify both natural and anthropogenic heat and hydrologic inputs to streams.
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Stream temperature‐equilibrium temperature relationship
Water Resources Research, 2003Co-Authors: Travis Bogan, Omid Mohseni, Heinz G. StefanAbstract:[1] Equilibrium temperature is the water temperature at which the sum of all heat fluxes through the water surface is zero. It can be calculated from weather data. Mean weekly stream temperature was found to be linearly related to mean weekly equilibrium temperature above 0°C. The slopes and intercepts of the linear relationship were used to identify effects of shading, sheltering, cold water inputs (groundwater, meltwater, and deep reservoir releases) and warm water inputs (wastewater, cooling water, and lake surface water). The linearity hypothesis was confirmed for data from 596 U.S. Geological Survey stream gaging stations in the eastern and central United States. For approximately 15% (89 of 596, NSC ≥ 0.90) of stream gaging stations, weekly equilibrium temperature was a good estimator of weekly stream temperature with zero wind sheltering and sun shading. With sheltering and shading the number rose to 26% (156 of 596). For these streams the heat exchange through the water surface has the most controlling effect on stream temperatures. For the remaining 74% of streams the relationship between weekly stream temperature and weekly equilibrium temperature was also linear, but its slope was significantly less than 1.0 (even after calibration for shading and sheltering), indicating that processes other than surface heat exchange have an influence. Cold water inflows were dominant for 8% (46 of 596) of stream gaging sites. Less than 5% of all stream gaging stations showed evidence of unnatural heat inputs. Fitting an equilibrium temperature linearly to recorded stream temperatures, e.g., at a weekly timescale, can be of use to project stream temperatures under different weather-climate scenarios or to identify both natural and anthropogenic heat and hydrologic inputs to streams.
Omid Mohseni - One of the best experts on this subject based on the ideXlab platform.
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stream temperature equilibrium temperature relationship
Water Resources Research, 2003Co-Authors: Travis Bogan, Omid Mohseni, Heinz G. StefanAbstract:[1] Equilibrium temperature is the water temperature at which the sum of all heat fluxes through the water surface is zero. It can be calculated from weather data. Mean weekly stream temperature was found to be linearly related to mean weekly equilibrium temperature above 0°C. The slopes and intercepts of the linear relationship were used to identify effects of shading, sheltering, cold water inputs (groundwater, meltwater, and deep reservoir releases) and warm water inputs (wastewater, cooling water, and lake surface water). The linearity hypothesis was confirmed for data from 596 U.S. Geological Survey stream gaging stations in the eastern and central United States. For approximately 15% (89 of 596, NSC ≥ 0.90) of stream gaging stations, weekly equilibrium temperature was a good estimator of weekly stream temperature with zero wind sheltering and sun shading. With sheltering and shading the number rose to 26% (156 of 596). For these streams the heat exchange through the water surface has the most controlling effect on stream temperatures. For the remaining 74% of streams the relationship between weekly stream temperature and weekly equilibrium temperature was also linear, but its slope was significantly less than 1.0 (even after calibration for shading and sheltering), indicating that processes other than surface heat exchange have an influence. Cold water inflows were dominant for 8% (46 of 596) of stream gaging sites. Less than 5% of all stream gaging stations showed evidence of unnatural heat inputs. Fitting an equilibrium temperature linearly to recorded stream temperatures, e.g., at a weekly timescale, can be of use to project stream temperatures under different weather-climate scenarios or to identify both natural and anthropogenic heat and hydrologic inputs to streams.
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Stream temperature‐equilibrium temperature relationship
Water Resources Research, 2003Co-Authors: Travis Bogan, Omid Mohseni, Heinz G. StefanAbstract:[1] Equilibrium temperature is the water temperature at which the sum of all heat fluxes through the water surface is zero. It can be calculated from weather data. Mean weekly stream temperature was found to be linearly related to mean weekly equilibrium temperature above 0°C. The slopes and intercepts of the linear relationship were used to identify effects of shading, sheltering, cold water inputs (groundwater, meltwater, and deep reservoir releases) and warm water inputs (wastewater, cooling water, and lake surface water). The linearity hypothesis was confirmed for data from 596 U.S. Geological Survey stream gaging stations in the eastern and central United States. For approximately 15% (89 of 596, NSC ≥ 0.90) of stream gaging stations, weekly equilibrium temperature was a good estimator of weekly stream temperature with zero wind sheltering and sun shading. With sheltering and shading the number rose to 26% (156 of 596). For these streams the heat exchange through the water surface has the most controlling effect on stream temperatures. For the remaining 74% of streams the relationship between weekly stream temperature and weekly equilibrium temperature was also linear, but its slope was significantly less than 1.0 (even after calibration for shading and sheltering), indicating that processes other than surface heat exchange have an influence. Cold water inflows were dominant for 8% (46 of 596) of stream gaging sites. Less than 5% of all stream gaging stations showed evidence of unnatural heat inputs. Fitting an equilibrium temperature linearly to recorded stream temperatures, e.g., at a weekly timescale, can be of use to project stream temperatures under different weather-climate scenarios or to identify both natural and anthropogenic heat and hydrologic inputs to streams.
Ling Liu - One of the best experts on this subject based on the ideXlab platform.
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CPU load shedding for binary stream joins
Knowledge and Information Systems, 2007Co-Authors: Bugra Gedik, Kun-lung Wu, Philip S Yu, Ling LiuAbstract:We present an adaptive load shedding approach for windowed stream joins. In contrast to the conventional approach of dropping tuples from the input streams, we explore the concept of selective processing for load shedding. We allow stream tuples to be stored in the windows and shed excessive CPU load by performing the join operations, not on the entire set of tuples within the windows, but on a dynamically changing subset of tuples that are learned to be highly beneficial. We support such dynamic selective processing through three forms of runtime adaptations : adaptation to input stream rates, adaptation to time correlation between the streams and adaptation to join directions. Our load shedding approach enables us to integrate utility-based load shedding with time correlation-based load shedding. Indexes are used to further speed up the execution of stream joins. Experiments are conducted to evaluate our adaptive load shedding in terms of output rate and utility. The results show that our selective processing approach to load shedding is very effective and significantly outperforms the approach that drops tuples from the input streams.
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adaptive load shedding for windowed stream joins
Conference on Information and Knowledge Management, 2005Co-Authors: Bugra Gedik, Kun-lung Wu, Philip S Yu, Ling LiuAbstract:We present an adaptive load shedding approach for windowed stream joins. In contrast to the conventional approach of dropping tuples from the input streams, we explore the concept of selective processing for load shedding. We allow stream tuples to be stored in the windows and shed excessive CPU load by performing the join operations, not on the entire set of tuples within the windows, but on a dynamically changing subset of tuples that are learned to be highly beneficial. We support such dynamic selective processing through three forms of runtime adaptations: adaptation to input stream rates, adaptation to time correlation between the streams and adaptation to join directions. Indexes are used to further speed up the execution of stream joins. Experiments are conducted to evaluate our adaptive load shedding in terms of output rate. The results show that our selective processing approach to load shedding is very effective and significantly outperforms the approach that drops tuples from the input streams.
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CIKM - Adaptive load shedding for windowed stream joins
Proceedings of the 14th ACM international conference on Information and knowledge management - CIKM '05, 2005Co-Authors: Buğgra Gedik, Ling LiuAbstract:We present an adaptive load shedding approach for windowed stream joins. In contrast to the conventional approach of dropping tuples from the input streams, we explore the concept of selective processing for load shedding. We allow stream tuples to be stored in the windows and shed excessive CPU load by performing the join operations, not on the entire set of tuples within the windows, but on a dynamically changing subset of tuples that are learned to be highly beneficial. We support such dynamic selective processing through three forms of runtime adaptations: adaptation to input stream rates, adaptation to time correlation between the streams and adaptation to join directions. Indexes are used to further speed up the execution of stream joins. Experiments are conducted to evaluate our adaptive load shedding in terms of output rate. The results show that our selective processing approach to load shedding is very effective and significantly outperforms the approach that drops tuples from the input streams.
Mamoru Miyamoto - One of the best experts on this subject based on the ideXlab platform.
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increase in stream temperature related to anthropogenic heat input from urban wastewater
Journal of Hydrology, 2007Co-Authors: Tsuyoshi Kinouchi, Hiroshi Yagi, Mamoru MiyamotoAbstract:Summary To better understand long-term temperature changes in urban streams, we investigated stream temperatures in the central Tokyo area and its suburbs from 1978 through 1998. Stream temperature data were analyzed together with data on thermal effluents of urban wastewater and air temperature for the same period. Statistical analyses indicated that the stream temperature in winter and early spring increased at a rate of 0.11–0.21 °C/year in segments that had a considerable increase in wastewater heat input over the same period. These segments showed an appreciable change in the relationship between air temperature and stream temperature, which suggests that the increase in anthropogenic heat input from wastewater was the main cause of the long-term increase in stream temperature. Other possible factors such as increasing air temperature and heat exchange with seawater were found to have comparatively minor influences.